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--- |
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tags: |
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- flair |
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- token-classification |
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- sequence-tagger-model |
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language: de |
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datasets: |
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- legal |
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widget: |
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- text: "Herr W. verstieß gegen § 36 Abs. 7 IfSG." |
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--- |
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## NER for German Legal Text in Flair (default model) |
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This is the legal NER model for German that ships with [Flair](https://github.com/flairNLP/flair/). |
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F1-Score: **96,35** (LER German dataset) |
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Predicts 19 tags: |
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| **tag** | **meaning** | |
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|---------------------------------|-----------| |
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| AN | Anwalt | |
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| EUN | Europäische Norm | |
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| GS | Gesetz | |
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| GRT | Gericht | |
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| INN | Institution | |
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| LD | Land | |
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| LDS | Landschaft | |
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| LIT | Literatur | |
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| MRK | Marke | |
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| ORG | Organisation | |
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| PER | Person | |
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| RR | Richter | |
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| RS | Rechtssprechung | |
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| ST | Stadt | |
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| STR | Straße | |
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| UN | Unternehmen | |
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| VO | Verordnung | |
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| VS | Vorschrift | |
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| VT | Vertrag | |
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Based on [Flair embeddings](https://www.aclweb.org/anthology/C18-1139/) and LSTM-CRF. |
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More details on the Legal NER dataset [here](https://github.com/elenanereiss/Legal-Entity-Recognition) |
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--- |
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### Demo: How to use in Flair |
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Requires: **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`) |
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```python |
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from flair.data import Sentence |
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from flair.models import SequenceTagger |
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# load tagger |
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tagger = SequenceTagger.load("flair/ner-german-legal") |
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# make example sentence (don't use tokenizer since Rechtstexte are badly handled) |
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sentence = Sentence("Herr W. verstieß gegen § 36 Abs. 7 IfSG.", use_tokenizer=False) |
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# predict NER tags |
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tagger.predict(sentence) |
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# print sentence |
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print(sentence) |
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# print predicted NER spans |
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print('The following NER tags are found:') |
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# iterate over entities and print |
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for entity in sentence.get_spans('ner'): |
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print(entity) |
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``` |
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This yields the following output: |
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``` |
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Span [2]: "W." [− Labels: PER (0.9911)] |
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Span [5,6,7,8,9]: "§ 36 Abs. 7 IfSG." [− Labels: GS (0.5353)] |
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``` |
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So, the entities "*W.*" (labeled as a **person**) and "*§ 36 Abs. 7 IfSG*" (labeled as a **Gesetz**) are found in the sentence "*Herr W. verstieß gegen § 36 Abs. 7 IfSG.*". |
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--- |
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### Training: Script to train this model |
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The following Flair script was used to train this model: |
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```python |
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from flair.data import Corpus |
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from flair.datasets import LER_GERMAN |
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from flair.embeddings import WordEmbeddings, StackedEmbeddings, FlairEmbeddings |
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# 1. get the corpus |
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corpus: Corpus = LER_GERMAN() |
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# 2. what tag do we want to predict? |
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tag_type = 'ner' |
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# 3. make the tag dictionary from the corpus |
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tag_dictionary = corpus.make_tag_dictionary(tag_type=tag_type) |
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# 4. initialize each embedding we use |
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embedding_types = [ |
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# GloVe embeddings |
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WordEmbeddings('de'), |
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# contextual string embeddings, forward |
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FlairEmbeddings('de-forward'), |
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# contextual string embeddings, backward |
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FlairEmbeddings('de-backward'), |
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] |
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# embedding stack consists of Flair and GloVe embeddings |
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embeddings = StackedEmbeddings(embeddings=embedding_types) |
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# 5. initialize sequence tagger |
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from flair.models import SequenceTagger |
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tagger = SequenceTagger(hidden_size=256, |
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embeddings=embeddings, |
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tag_dictionary=tag_dictionary, |
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tag_type=tag_type) |
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# 6. initialize trainer |
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from flair.trainers import ModelTrainer |
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trainer = ModelTrainer(tagger, corpus) |
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# 7. run training |
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trainer.train('resources/taggers/ner-german-legal', |
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train_with_dev=True, |
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max_epochs=150) |
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``` |
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--- |
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### Cite |
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Please cite the following papers when using this model. |
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``` |
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@inproceedings{leitner2019fine, |
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author = {Elena Leitner and Georg Rehm and Julian Moreno-Schneider}, |
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title = {{Fine-grained Named Entity Recognition in Legal Documents}}, |
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booktitle = {Semantic Systems. The Power of AI and Knowledge |
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Graphs. Proceedings of the 15th International Conference |
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(SEMANTiCS 2019)}, |
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year = 2019, |
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pages = {272--287}, |
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pdf = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-33220-4_20.pdf}} |
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``` |
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``` |
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@inproceedings{akbik2018coling, |
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title={Contextual String Embeddings for Sequence Labeling}, |
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author={Akbik, Alan and Blythe, Duncan and Vollgraf, Roland}, |
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booktitle = {{COLING} 2018, 27th International Conference on Computational Linguistics}, |
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pages = {1638--1649}, |
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year = {2018} |
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} |
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``` |
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--- |
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### Issues? |
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The Flair issue tracker is available [here](https://github.com/flairNLP/flair/issues/). |
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